Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images

doi:10.1007/s00330-018-5725-3

	Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images
	Niu, Jianxing 1; Zhang, Shuaitong 2,3; Ma, Shunchang 1; Diao, Jinfu 1; Zhou, Wenjianlong 1; Tian, Jie 2,3,4; Zang, Yali2,3 ; Jia, Wang 1
刊名	EUROPEAN RADIOLOGY
	2019-03-01
卷号	29 期号:3 页码:1625-1634
关键词	Pituitary adenomas Cavernous sinus Neoplasm invasion Nomogram Support vector machine
ISSN号	0938-7994
DOI	10.1007/s00330-018-5725-3
通讯作者	Zang, Yali(yali.zang@ia.ac.cn) ; Jia, Wang(jwttyy@126.com)
英文摘要	ObjectivesTo predict cavernous sinus (CS) invasion by pituitary adenomas (PAs) pre-operatively using a radiomics method based on contrast-enhanced T1 (CE-T1) and T2-weighted magnetic resonance (MR) imaging.MethodsA total of 194 patients with Knosp grade two and three PAs (training set: n = 97; test set: n = 97) were enrolled in this retrospective study. From CE-T1 and T2 MR images, 2553 quantitative imaging features were extracted. To select the most informative features, least absolute shrinkage and selection operator (LASSO) was performed. Subsequently, a linear support vector machine (SVM) was used to fit the predictive model. Furthermore, a nomogram was constructed by incorporating clinico-radiological risk factors and radiomics signature, and the clinical usefulness of the nomogram was validated using decision curve analysis (DCA).ResultsThree imaging features were selected in the training set, based on which the radiomics model yielded area under the curve (AUC) values of 0.852 and 0.826 for the training and test sets. The nomogram based on the radiomics signature and the clinico-radiological risk factors yielded an AUC of 0.899 in the training set and 0.871 in the test set.ConclusionsThe nomogram developed in this study might aid neurosurgeons in the pre-operative prediction of CS invasion by Knosp grade two and three PAs, which might contribute to creating surgical strategies.Key Points center dot Pre-operative diagnosis of CS invasion by PAs might affect creating surgical strategies center dot MRI might help for diagnosis of CS invasion by PAs before surgery center dot Radiomics might improve the CS invasion detection by MR images.
资助项目	National Key Research and Development Program of China[2017YFA0205200] ; National Key Research and Development Program of China[2017YFC1308700] ; National Key Research and Development Program of China[2106YFC0103702] ; National Key Research and Development Program of China[2016YFA0201401] ; National Key Research and Development Program of China[2017YFC1308701] ; National Key Research and Development Program of China[2017YFC1309100] ; National Key Research and Development Program of China[2016CZYD0001] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81501616] ; National Natural Science Foundation of China[81671851] ; Beijing excellent talent funding project[2016000037591G246] ; Beijing Municipal Science & Technology Commission[Z161100002616022] ; Beijing Municipal Science & Technology Commission[Z171100000117023] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-SW-STS-160] ; Instrument Developing Project of the Chinese Academy of Sciences[YZ201502]
WOS关键词	TRANSSPHENOIDAL APPROACH ; TEXTURE ; CLASSIFICATION ; INFORMATION ; RECURRENCE ; SELECTION ; RESECTION ; SURVIVAL ; FEATURES ; SPACE
WOS研究方向	Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000457396100060
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing excellent talent funding project ; Beijing Municipal Science & Technology Commission ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences ; Instrument Developing Project of the Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/25299]
专题	中国科学院自动化研究所
通讯作者	Zang, Yali; Jia, Wang
作者单位	1.Capital Med Univ, Beijing Tiantan Hosp, Neurosurg, Beijing 100050, Peoples R China 2.Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100080, Peoples R China 4.Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Niu, Jianxing,Zhang, Shuaitong,Ma, Shunchang,et al. Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images[J]. EUROPEAN RADIOLOGY,2019,29(3):1625-1634.
APA	Niu, Jianxing.,Zhang, Shuaitong.,Ma, Shunchang.,Diao, Jinfu.,Zhou, Wenjianlong.,...&Jia, Wang.(2019).Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images.EUROPEAN RADIOLOGY,29(3),1625-1634.
MLA	Niu, Jianxing,et al."Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images".EUROPEAN RADIOLOGY 29.3(2019):1625-1634.